Radiography is an essential tool in security inspection, and typically implemented in the following process. First, a radiography device scans luggage and generates an image of the luggage. An inspector checks the image, manually marks regions of suspicious objects, and adds semantic description of these regions, such as “lighter,” and “a bottle of wine.” This process relies largely on human factor, and may leave some dangerous article undetected when the dangerous article occurs in a very low frequency, or when the inspector has inadequate experience or is influenced by factors including fatigue. This will lead to serious aftermath.
A typical measurement to solve the above problem is to primarily rely on automatic detection while interaction between the inspector and the device is auxiliary. The automatic detection technology is not satisfactory nowdays. Some typical techniques, such as explosive detection, and high-density alarm, cannot satisfactorily meet the application requirements. This is because that there are certain technical limits, such as object aliasing caused by perspective overlapping in DEDR (Dual Energy Digital Radiography), and on the other hand, research in this aspect is few, while updated technology like DECT (Dual Energy Computed Tomography) needs support from new detection algorithms.
DECT is a preferable solution to the above problem. DECT is developed from DR and CT technologies, and can obtain effective atomic number and equivalent electron density inside a scanned object while acquiring 3D structure information of the object. Accordingly, DECT provides possibility of better understanding of the scanned content through 3D data. However, the current research is focused on detection of specific objects, and mainly relies on pixel-level information of density and atomic number. Thus, there is a lack of recognition of “object” information.